InSysBio announces its participation in JuliaCon Local Paris 2025 which is to be held from October 2-3, 2025 at the National Conservatory of Arts and Crafts, Paris, France. Ivan Borisov, Senior Software Developer at InSysBio, will present a poster in frames of the Conference, namely:
Ivan Borisov will give a talk based on the poster on October 3, 10:39–10:42 (Europe/Paris), at the Coffee room. This talk showcases how LikelihoodProfiler.jl fits into the model calibration workflow, integrates with the SciML ecosystem, and leverages Julia's parallel computing features. A Systems Biology model will be used to illustrate the analysis and demonstrate the overall workflow.
About InSysBio
InSysBio is a group of Quantitative Systems Pharmacology (QSP) companies located in Limassol, Cyprus (INSYSBIO CY Ltd) and Edinburgh, UK (INSYSBIO UK LIMITED). InSysBio was founded in 2004 and has an extensive track record of helping pharmaceutical companies to make right decisions on the critical stages of drug research and development by application of QSP modeling. InSysBio’s cutting-edge QSP approach has already become a part of the drug development process implemented by our strategic partners: there are more than 100 completed projects in collaboration with leaders of pharmaceutical industry and innovative biotech companies. For more information about InSysBio, its solutions and services, visit www.insysbio.com
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14 Jan 2021 14:28
InSysBio to publish the new article on identifiability analysis in PLOS Computational Biology
[Moscow – 11.01.2021] InSysBio, one of the world’s pioneers of Quantitative Systems Pharmacology (QSP) modeling, has published its recent scientific research on identifiability in PLOS Computational Biology.
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26 Jan 2021 13:14
InSysBio to announce the upgrade of its SbmlViewer application to version 0.2.7
[Moscow – 26.01.2021] InSysBio, one of the world’s pioneers of Quantitative Systems Pharmacology (QSP) modeling, launces the new version of its SbmlViewer open project. Generally, SbmlViewer represents a tool for fast and easy reading of biological models written in SBML format.
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